Keep it simple: ranking health states yields values similar to cardinal measurement approaches

Abstract OBJECTIVES: To examine the relationship between ordinal and cardinal valuation of health states. STUDY DESIGN AND SETTING: We analyzed rank, visual analog scale (VAS), and time trade-off (TTO) responses for 52 health states defined using the EQ-5D classification system developed by the EuroQol Group. We analyzed 179,431 responses from 11,483 subjects in eight countries: Slovenia, Argentina, Denmark, Japan, Netherlands, Spain, United Kingdom, and United States. We first compared responses across methods by frequency of ties and values below dead. Ordinal associations between methods were evaluated using Spearman's correlation and Kendall's tau. Next, we estimated numerical values from rank responses using country-specific conditional logit models. After anchoring predicted values on a common scale, we further investigated the cardinal relationships between rank, VAS, and TTO-based values using Pearson's rho and quadratic regression. RESULTS: For each country, rank responses are less likely than TTO responses to be tied and to indicate that states are worse than dead. In all countries, rank responses show a strong linear correlation with both TTO (Pearson's rho=0.88-0.99) and VAS (rho=0.91-0.98) responses. However, rank-ba

Comparative effectiveness of personalized lifestyle management strategies for cardiovascular disease risk reduction

Background-Evidence shows that healthy diet, exercise, smoking interventions, and stress reduction reduce cardiovascular disease risk. We aimed to compare the effectiveness of these lifestyle interventions for individual risk profiles and determine their rank order in reducing 10-year cardiovascular disease risk. Methods and Results-We computed risks using the American College of Cardiology/American Heart Association Pooled Cohort Equations for a variety of individual profiles. Using published literature on risk factor reductions through diverse lifestyle interventions-group therapy for stopping smoking, Mediterranean diet, aerobic exercise (walking), and yoga-we calculated the risk reduction through each of these interventions to determine the strategy associated with the maximum benefit for each profile. Sensitivity analyses were conducted to test the robustness of the results. In the base-case analysis, yoga was associated with the largest 10-year cardiovascular disease risk reductions (maximum absolute reduction 16.7% for the highest-risk individuals). Walking generally ranked second (max 11.4%), followed by Mediterranean diet (max 9.2%), and group therapy for smoking (max 1.6%). If the individual was a current smoker and successfully quit smoking (ie, achieved complete smoking cessation), then stopping smoking yielded the largest reduction. Probabilistic and 1-way sensitivity analysis confirmed the demonstrated trend. Conclusions-This study reports the comparative effectiveness of several forms of lifestyle modifications and found smoking cessation and yoga to be the most effective forms of cardiovascular disease prevention. Future research should focus on patient adherence to personalized therapies, cost-effectiveness of these strategies, and the potential for enhanced benefit when interventions are performed simultaneously rather than as single measures

Estimating the distribution of morbidity and mortality of childhood diarrhea, measles, and pneumonia by wealth group in low- and middle-income countries

__Background:__ Equitable access to vaccines has been suggested as a priority for low- and middle-income countries (LMICs). However, it is unclear whether providing equitable access is enough to ensure health equity. Furthermore, disaggregated data on health outcomes and benefits gained across population subgroups are often unavailable. This paper develops a model to estimate the distribution of childhood disease cases and deaths across socioeconomic groups, and the potential benefits of three vaccine programs in LMICs. __Methods:__ For each country and for three diseases (diarrhea, measles, pneumonia), we estimated the distributions of cases and deaths that would occur across wealth quintiles in the absence of any immunization or treatment programs, using both the prevalence and relative risk of a set of risk and prognostic factors. Building on these baseline estimates, we examined what might be the impact of three vaccines (first dose of measles, pneumococcal conjugate, and rotavirus vaccines), under five scenarios based on different sets of quintile-specific immunization coverage and disease treatment utilization rates. __Results:__ Due to higher prevalence of risk factors among the poor, disproportionately more disease cases and deaths would occur among the two lowest wealth quintiles for all three diseases when vaccines or treatment are unavailable. Country-specific context, including how the baseline risks, immunization coverage, and treatment utilization are currently distributed across quintiles, affects how different policies translate into changes in cases and deaths distribution. __Conclusions:__ Our study highlights several factors that would substantially contribute to the unequal distribution of childhood diseases, and finds that merely ensuring equal access to vaccines will not reduce the health outcomes gap across wealth quintiles. Such information can inform policies and planning of programs that aim to improve equitable delivery of healthcare services

Measuring health and economic wellbeing in the Sustainable Development Goals era: development of a poverty-free life expectancy metric and estimates for 90 countries

Background: The Sustainable Development Goals (SDGs), adopted in September, 2015, emphasise the link between health and economic development policies. Despite this link, and the multitude of targets and indicators in the SDGs and other initiatives, few monitoring tools explicitly incorporate measures of both health and economic status. Here we propose poverty-free life expectancy (PFLE) as a new metric that uses widely available data to provide a composite measure of population health and economic wellbeing. Methods: We developed a population-level measure of PFLE and computed this summary measure for 90 countries with available data. Specifically, we used Sullivan's method, as in many health expectancy measures, to incorporate the prevalence of poverty by age and sex from household economic surveys into demographic life tables based on mortality rates from the 2015 Global Burden of Disease Study (GBD). For comparison, we also recalculated all PFLE measures using life tables from WHO and the UN. PFLE estimates for each country, stratified by sex, are the average number of poverty-free years a person could expect to live if exposed to current mortality rates and poverty prevalence in that country. Findings: The average PFLE in the 90 countries included in this study was 66·0 years (95% uncertainty interval [UI] 64·5–67·3) for females and 61·6 years (60·1–62·9) for males, whereas life expectancy estimates were 76·3 years (95% UI 74·0–78·2) for females and 71·0 years (68·7–73·0) for males. PFLE varied widely between countries, ranging from 9·9 years (95% UI 9·1–10·5) for both sexes combined in Malawi, to 83·2 years (83·0–83·5) in Iceland, the latter differing only marginally from life expectancy in that country. In 67 of 90 countries, the difference between life expectancy and PFLE was greater for females than for males, indicating that women generally live more years of life in poverty than men do. Results were consistent when using GBD, WHO, or UN life tables. Interpretation: Differences in PFLE between countries are substantially greater than differences in life expectancy. Despite general improvements in survival in most regions of the world in the past decades, the focus in the SDG era on ending poverty brings into sharp relief the importance of ensuring that years of added life are lived with at least a minimum standard of economic wellbeing. Although summary measures of population health provide overall measures of survivorship and functional health, our new measure of PFLE provides complementary information that can inform and benchmark policies seeking to improve both health and economic wellbeing. Funding: None

Component-based design of multi-objective evolutionary algorithms using the Tigon optimization library

Multi-objective optimization problems involve several conflicting objectives that have to be optimized simultaneously. Generating a complete Pareto-optimal front (POF) can be computationally expensive or even infeasible, and for that reason there has been an enormous interest in using multi-objective evolutionary algorithms (MOEAs), which are known to generate a good approximation of the POF. MOEAs can be difficult to implement, and even for experienced optimization experts it can be a very time consuming task. For this reason several optimization libraries exist in the literature, providing off-the-shelf access to the most popular MOEAs. Some optimization libraries also provide a framework to design MOEAs. However, existing frameworks can be too stringent and do not provide sufficient flexibility for the design of more sophisticated MOEAs. To address this, a recently proposed optimization library, known as Tigon, features a component-based framework for the design of MOEAs with a focus on flexibility and re-usability. This paper demonstrates the generality of this new framework by showing how to implement different types of MOEAs, covering several paradigms in evolutionary computation. The work in this paper serves as a guide for researchers, and others alike, to build their own MOEAs by using the Tigon optimization library

Methods for constrained optimization of expensive mixed-integer multi-objective problems, with application to an internal combustion engine design problem

Engineering design optimization problems increasingly require computationally expensive high-fidelity simulation models to evaluate candidate designs. The evaluation budget may be small, limiting the effectiveness of conventional multi-objective evolutionary algorithms. Bayesian optimization algorithms (BOAs) are an alternative approach for expensive problems but are underdeveloped in terms of support for constraints and non-continuous design variables—both of which are prevalent features of real-world design problems. This study investigates two constraint handling strategies for BOAs and introduces the first BOA for mixed-integer problems, intended for use on a real-world engine design problem. The new BOAs are empirically compared to their closest competitor for this problem—the multi-objective evolutionary algorithm NSGA-II, itself equipped with constraint handling and mixed-integer components. Performance is also analysed on two benchmark problems which have similar features to the engine design problem, but are computationally cheaper to evaluate. The BOAs offer statistically significant convergence improvements of between 5.9% and 31.9% over NSGA-II across the problems on a budget of 500 design evaluations. Of the two constraint handling methods, constrained expected improvement offers better convergence than the penalty function approach. For the engine problem, the BOAs identify improved feasible designs offering 36.4% reductions in nitrogen oxide emissions and 2.0% reductions in fuel consumption when compared to a notional baseline design. The use of constrained mixed-integer BOAs is recommended for expensive engineering design optimization problems

Light scattering from disordered overlayers of metallic nanoparticles

We develop a theory for light scattering from a disordered layer of metal nanoparticles resting on a sample. Averaging over different disorder realizations is done by a coherent potential approximation. The calculational scheme takes into account effects of retardation, multipole excitations, and interactions with the sample. We apply the theory to a system similar to the one studied experimentally by Stuart and Hall [Phys. Rev. Lett. {\bf 80}, 5663 (1998)] who used a layered Si/SiO$_2$/Si sample. The calculated results agree rather well with the experimental ones. In particular we find conspicuous maxima in the scattering intensity at long wavelengths (much longer than those corresponding to plasmon resonances in the particles). We show that these maxima have their origin in interference phenomena in the layered sample.Comment: 19 pages, 12 figure

Field testing for toxic algae with a microarray: initial results from the MIDTAL project

One of the key tasks in the project MIDTAL (MIcroarrays for the Detection of Toxic ALgae) is to demonstrate the applicability of microarrays to monitor harmful algae across a broad range of ecological niches and toxic species responsible for harmful algal events. Water samples are collected from a series of sites used in national phytoplankton and biotoxin monitoring programmes across Europe. The samples are filtered; the rRNA is extracted, labelled with a fluorescent dye and applied to a microarray chip. The signal intensity from >120 probes previously spotted on the chip is measured and analysed. Preliminary results comparing microarray signal intensities with actual field counts are presented

Field testing for toxic algae with a microarray: initial results from the MIDTAL project

One of the key tasks in MIDTAL (MIcroarrays for the Detection of Toxic ALgae) is to demonstrate the applicability of microarrays to monitor harmful algae across a broad range of ecological niches and toxic species responsible for harmful algal events. Water samples are collected from a series of sites used in national phytoplankton and biotoxin monitoring across Europe. The samples are filtered; rRNA is extracted, labelled with a fluorescent dye and applied to a microarray chip. The signal intensity from >120 probes previously spotted on the chip is measured and analysed. Preliminary results comparing microarray signal intensities with actual field counts are presented.Versión del edito

Liger : a cross-platform open-source integrated optimization and decision-making environment

Real-world optimization problems involving multiple conflicting objectives are commonly best solved using multi-objective optimization as this provides decision-makers with a family of trade-off solutions. However, the complexity of using multi-objective optimization algorithms often impedes the optimization process. Knowing which optimization algorithm is the most suitable for the given problem, or even which setup parameters to pick, requires someone to be an optimization specialist. The lack of supporting software that is readily available, easy to use and transparent can lead to increased design times and increased cost. To address these challenges, Liger is presented. Liger has been designed for ease of use in industry by non-specialists in optimization. The user interacts with Liger via a visual programming language to create an optimization workflow, enabling the user to solve an optimization problem. Liger contains a novel optimization library known as Tigon. The library utilizes the concept of design patterns to enable the composition of optimization algorithms by making use of simple reusable operator nodes. The library offers a varied range of multi-objective evolutionary algorithms which cover different paradigms in evolutionary computation; and supports a wide variety of problem types, including support for using more than one programming language at a time to implement the optimization model. Additionally, Liger functionality can be easily extended by plugins that provide access to state-of-the-art visualization tools and are responsible for managing the graphical user interface. Lastly, new user-driven interactive capabilities are shown to facilitate the decision-making process and are demonstrated on a control engineering optimization problem